Teaching

Current courses

Hotter Ecology: Climate change impacts from individuals to ecosystems (CONS 449C 203) -Anthropogenic climate change has already raised the global temperature nearly one degree, with far more radical warming predicted in the coming decades. With this elevated temperature regime come shifts in frosts, precipitation, storms and extremes. Alongside these major physical impacts many aspects of ecological systems are changing. This course will build on the fundamental organizing units of ecology: individuals, populations, species, communities and ecosystems to build a framework to understand what has shifted in the last 40 years and what we may expect by the end of the century. For more information, see here.

Experimental design and hierarchical model building with Bayesian inference (507C 202) - This class will cover the fundamentals of model building with a focus on regression and hierarchical models, for data gathered from experiments, observational studies and meta-analytic approaches. The course will cover experimental design, model building for causal inference, hierarchical models, missing data, model verification and validation, and randomized experiments. Much of the course will focus on how to build and use test data to improve study design. Inference will be Bayesian-focused. More info here.

Open to students who have taken FRST 430, BIOL 501 or equivalent or by permission of the instructor. Students must be comfortable with R. Topics covered require knowledge of basic statistics through linear and logistic regression approaches (these topics will NOT be covered in the class).

Past courses

Introduction to Biological Statistics (Harvard OEB 153, co-taught with Professor John Wakeley) - Introduction to probability and statistics, with dual concern for analytical thinking and data analysis.The fundamentals of R will be covered, then this software environment will be used to analyze data and make statistical inferences. Ecological and genetic data will be the primary focus of applications. Analytical thinking modules will cover the theory of probability, statistical distributions, and the principles of statistical inference. You will will learn how to defend your claims and not be fooled by quantitative arguments.

Introduction to experimental design and model building for ecologists and evolutionary biologists (Harvard OEB 201) - This class will cover the fundamentals of model building with a focus on regression, for data gathered from experiments as well as other approaches. The course will move briskly through basic statistics (averages, standard errors) and linear regression then focus on experimental design, model building and causal inference, covering sample size decisions, missing data, model verification and validation, and randomized experiments. Inference will be Bayesian-focused.

Modern Conservation Biology (Harvard OEB 216) - Readings (mainly from the scientific literature) and discussion of what defines and theoretically underpins the field of conservation biology - though discussion is on the current version of the field, readings will span its development over the last 50+ years.

Wilderness & Society (Dartmouth Environmental Studies) - This course examines the intersection of wilderness and humans by readings of wilderness writers, activists, conservation scientists and journalists. It begins with reading Muir's and his followers' work, as well as examining contemporary wilderness stories (Into the Wild and Accidental Explorer). It then follows the role of such work in the current conservation and wilderness preservation movement, considering the roles of activists, writers and scientists to our current definition of wilderness.

Students learning about the Nutrient Network study before biomass clipping in 2008.